Impact of traffic congestion on spatial access to healthcare services in Nairobi
Impact of traffic congestion on spatial access to healthcare services in Nairobi
Background: Geographic accessibility is an important determinant of healthcare utilization and is critical for achievement of universal health coverage. Despite the high disease burden and severe traffic congestion in many African cities, few studies have assessed how traffic congestion impacts geographical access to healthcare facilities and to health professionals in these settings. In this study, we assessed the impact of traffic congestion on access to healthcare facilities, and to the healthcare professionals across the healthcare facilities.
Methods: Using data on health facilities obtained from the Ministry of Health in Kenya, we mapped 944 primary, 94 secondary and four tertiary healthcare facilities in Nairobi County. We then used traffic probe data to identify areas within a 15-, 30- and 45-min drive from each health facility during peak and off-peak hours and calculated the proportion of the population with access to healthcare in the County. We employed a 2-step floating catchment area model to calculate the ratio of healthcare and healthcare professionals to population during these times.
Results: During peak hours, <70% of Nairobi's 4.1 million population was within a 30-min drive from a health facility. This increased to >75% during off-peak hours. In 45 min, the majority of the population had an accessibility index of one health facility accessible to more than 100 people (<0.01) for primary health care facilities, one to 10,000 people for secondary facilities, and two health facilities per 100,000 people for tertiary health facilities. Of people with access to health facilities, a sub-optimal ratio of <4.45 healthcare professionals per 1,000 people was observed in facilities offering primary and secondary healthcare during peak and off-peak hours.
Conclusion: Our study shows access to healthcare being negatively impacted by traffic congestion, highlighting the need for multisectoral collaborations between urban planners, health sector and policymakers to optimize health access for the city residents. Additionally, growing availability of traffic probe data in African cities should enable similar analysis and understanding of healthcare access for city residents in other countries on the continent.
Nyamai, Mutono
c88301b3-e962-4e60-9d22-41e560d2de79
Wright, Jim A.
94990ecf-f8dd-4649-84f2-b28bf272e464
Mutunga, Mumbua
ce296f65-f6aa-4500-abc0-591ddf111081
Mutembei, Henry
98366d1f-2996-465f-8733-5e85e5603827
Thumbi, S.M.
b5751868-17cd-4b63-9ec1-6ba33c3c1c85
16 November 2022
Nyamai, Mutono
c88301b3-e962-4e60-9d22-41e560d2de79
Wright, Jim A.
94990ecf-f8dd-4649-84f2-b28bf272e464
Mutunga, Mumbua
ce296f65-f6aa-4500-abc0-591ddf111081
Mutembei, Henry
98366d1f-2996-465f-8733-5e85e5603827
Thumbi, S.M.
b5751868-17cd-4b63-9ec1-6ba33c3c1c85
Nyamai, Mutono, Wright, Jim A., Mutunga, Mumbua, Mutembei, Henry and Thumbi, S.M.
(2022)
Impact of traffic congestion on spatial access to healthcare services in Nairobi.
Frontiers in Health Services, 2.
(doi:10.3389/frhs.2022.788173).
Abstract
Background: Geographic accessibility is an important determinant of healthcare utilization and is critical for achievement of universal health coverage. Despite the high disease burden and severe traffic congestion in many African cities, few studies have assessed how traffic congestion impacts geographical access to healthcare facilities and to health professionals in these settings. In this study, we assessed the impact of traffic congestion on access to healthcare facilities, and to the healthcare professionals across the healthcare facilities.
Methods: Using data on health facilities obtained from the Ministry of Health in Kenya, we mapped 944 primary, 94 secondary and four tertiary healthcare facilities in Nairobi County. We then used traffic probe data to identify areas within a 15-, 30- and 45-min drive from each health facility during peak and off-peak hours and calculated the proportion of the population with access to healthcare in the County. We employed a 2-step floating catchment area model to calculate the ratio of healthcare and healthcare professionals to population during these times.
Results: During peak hours, <70% of Nairobi's 4.1 million population was within a 30-min drive from a health facility. This increased to >75% during off-peak hours. In 45 min, the majority of the population had an accessibility index of one health facility accessible to more than 100 people (<0.01) for primary health care facilities, one to 10,000 people for secondary facilities, and two health facilities per 100,000 people for tertiary health facilities. Of people with access to health facilities, a sub-optimal ratio of <4.45 healthcare professionals per 1,000 people was observed in facilities offering primary and secondary healthcare during peak and off-peak hours.
Conclusion: Our study shows access to healthcare being negatively impacted by traffic congestion, highlighting the need for multisectoral collaborations between urban planners, health sector and policymakers to optimize health access for the city residents. Additionally, growing availability of traffic probe data in African cities should enable similar analysis and understanding of healthcare access for city residents in other countries on the continent.
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frhs-02-788173
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Accepted/In Press date: 25 October 2022
Published date: 16 November 2022
Identifiers
Local EPrints ID: 473935
URI: http://eprints.soton.ac.uk/id/eprint/473935
ISSN: 2813-0146
PURE UUID: 145d995e-d689-4860-a0a5-08a4b83ac76c
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Date deposited: 06 Feb 2023 17:32
Last modified: 17 Mar 2024 02:59
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Author:
Mutono Nyamai
Author:
Mumbua Mutunga
Author:
Henry Mutembei
Author:
S.M. Thumbi
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